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- _base_ = './htc_without_semantic_r50_fpn_1x_coco.py'
- model = dict(
- roi_head=dict(
- semantic_roi_extractor=dict(
- type='SingleRoIExtractor',
- roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
- out_channels=256,
- featmap_strides=[8]),
- semantic_head=dict(
- type='FusedSemanticHead',
- num_ins=5,
- fusion_level=1,
- num_convs=4,
- in_channels=256,
- conv_out_channels=256,
- num_classes=183,
- loss_seg=dict(
- type='CrossEntropyLoss', ignore_index=255, loss_weight=0.2))))
- data_root = 'data/coco/'
- img_norm_cfg = dict(
- mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
- train_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(
- type='LoadAnnotations', with_bbox=True, with_mask=True, with_seg=True),
- dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
- dict(type='RandomFlip', flip_ratio=0.5),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='Pad', size_divisor=32),
- dict(type='SegRescale', scale_factor=1 / 8),
- dict(type='DefaultFormatBundle'),
- dict(
- type='Collect',
- keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks', 'gt_semantic_seg']),
- ]
- test_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(
- type='MultiScaleFlipAug',
- img_scale=(1333, 800),
- flip=False,
- transforms=[
- dict(type='Resize', keep_ratio=True),
- dict(type='RandomFlip', flip_ratio=0.5),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='Pad', size_divisor=32),
- dict(type='ImageToTensor', keys=['img']),
- dict(type='Collect', keys=['img']),
- ])
- ]
- data = dict(
- train=dict(
- seg_prefix=data_root + 'stuffthingmaps/train2017/',
- pipeline=train_pipeline),
- val=dict(pipeline=test_pipeline),
- test=dict(pipeline=test_pipeline))
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